Discovery of small molecule agonists of the Relaxin Family Peptide Receptor 2.

The relaxin/insulin-like family peptide receptor 2 (RXFP2) belongs to the family of class A G-protein coupled receptors (GPCRs) and it is the only known target for the insulin-like factor 3 peptide (INSL3). The importance of this ligand-receptor pair in the development of the gubernacular ligament during the transabdominal phase of testicular descent is well established. More recently, RXFP2 has been implicated in maintaining healthy bone formation. In this report, we describe the discovery of a small molecule series of RXFP2 agonists. These compounds are highly potent, efficacious, and selective RXFP2 allosteric agonists that induce gubernacular invagination in mouse embryos, increase mineralization activity in human osteoblasts in vitro, and improve bone trabecular parameters in adult mice. The described RXFP2 agonists are orally bioavailable and display favorable pharmacokinetic properties, which allow for future evaluation of the therapeutic benefits of modulating RXFP2 activation in disease models.

Defining clinical outcome pathways.

Here, we propose a broad concept of 'Clinical Outcome Pathways' (COPs), which are defined as a series of key molecular and cellular events that underlie therapeutic effects of drug molecules. We formalize COPs as a chain of the following events: molecular initiating event (MIE) â†’ intermediate event(s) â†’ clinical outcome. We illustrate the concept with COP examples both for primary and alternative (i.e., drug repurposing) therapeutic applications. We also describe the elucidation of COPs for several drugs of interest using the publicly accessible Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways (ROBOKOP) biomedical knowledge graph-mining tool. We propose that broader use of COP uncovered with the help of biomedical knowledge graph mining will likely accelerate drug discovery and repurposing efforts.

NCATS Inxight Drugs: a comprehensive and curated portal for translational research.

The United States has a complex regulatory scheme for marketing drugs. Understanding drug regulatory status is a daunting task that requires integrating data from many sources from the United States Food and Drug Administration (FDA), US government publications, and other processes related to drug development. At NCATS, we created Inxight Drugs (https://drugs.ncats.io), a web resource that attempts to address this challenge in a systematic manner. NCATS Inxight Drugs incorporates and unifies a wealth of data, including those supplied by the FDA and from independent public sources. The database offers a substantial amount of manually curated literature data unavailable from other sources. Currently, the database contains 125 036 product ingredients, including 2566 US approved drugs, 6242 marketed drugs, and 9684 investigational drugs. All substances are rigorously defined according to the ISO 11238 standard to comply with existing regulatory standards for unique drug substance identification. A special emphasis was placed on capturing manually curated and referenced data on treatment modalities and semantic relationships between substances. A supplementary resource 'Novel FDA Drug Approvals' features regulatory details of newly approved FDA drugs. The database is regularly updated using NCATS Stitcher data integration tool that automates data aggregation and supports full data access through a RESTful API.

Critical Assessment of Artificial Intelligence Methods for Prediction of hERG Channel Inhibition in the "Big Data" Era.

The rise of novel artificial intelligence (AI) methods necessitates their benchmarking against classical machine learning for a typical drug-discovery project. Inhibition of the potassium ion channel, whose alpha subunit is encoded by the human ether-à-go-go-related gene (hERG), leads to a prolonged QT interval of the cardiac action potential and is a significant safety pharmacology target for the development of new medicines. Several computational approaches have been employed to develop prediction models for the assessment of hERG liabilities of small molecules including recent work using deep learning methods. Here, we perform a comprehensive comparison of hERG effect prediction models based on classical approaches (random forests and gradient boosting) and modern AI methods [deep neural networks (DNNs) and recurrent neural networks (RNNs)]. The training set (∼9000 compounds) was compiled by integrating the hERG bioactivity data from the ChEMBL database with experimental data generated from an in-house, high-throughput thallium flux assay. We utilized different molecular descriptors including the latent descriptors, which are real-value continuous vectors derived from chemical autoencoders trained on a large chemical space (>1.5 million compounds). The models were prospectively validated on ∼840 in-house compounds screened in the same thallium flux assay. The best results were obtained with the XGBoost method and RDKit descriptors. The comparison of models based only on latent descriptors revealed that the DNNs performed significantly better than the classical methods. The RNNs that operate on SMILES provided the highest model sensitivity. The best models were merged into a consensus model that offered superior performance compared to reference models from academic and commercial domains. Furthermore, we shed light on the potential of AI methods to exploit the big data in chemistry and generate novel chemical representations useful in predictive modeling and tailoring a new chemical space.

Identification of a Small-Molecule Inhibitor That Disrupts the SIX1/EYA2 Complex, EMT, and Metastasis.

Metastasis is the major cause of mortality for patients with cancer, and dysregulation of developmental signaling pathways can significantly contribute to the metastatic process. The Sine oculis homeobox homolog 1 (SIX1)/eyes absent (EYA) transcriptional complex plays a critical role in the development of multiple organs and is typically downregulated after development is complete. In breast cancer, aberrant expression of SIX1 has been demonstrated to stimulate metastasis through activation of TGFß signaling and subsequent induction of epithelial-mesenchymal transition (EMT). In addition, SIX1 can induce metastasis via non-cell autonomous means, including activation of GLI-signaling in neighboring tumor cells and activation of VEGFC-induced lymphangiogenesis. Thus, targeting SIX1 would be expected to inhibit metastasis while conferring limited side effects. However, transcription factors are notoriously difficult to target, and thus novel approaches to inhibit their action must be taken. Here we identified a novel small molecule compound, NCGC00378430 (abbreviated as 8430), that reduces the SIX1/EYA2 interaction. 8430 partially reversed transcriptional and metabolic profiles mediated by SIX1 overexpression and reversed SIX1-induced TGFß signaling and EMT. 8430 was well tolerated when delivered to mice and significantly suppressed breast cancer-associated metastasis in vivo without significantly altering primary tumor growth. Thus, we have demonstrated for the first time that pharmacologic inhibition of the SIX1/EYA2 complex and associated phenotypes is sufficient to suppress breast cancer metastasis. SIGNIFICANCE: These findings identify and characterize a novel inhibitor of the SIX1/EYA2 complex that reverses EMT phenotypes suppressing breast cancer metastasis.

Predicting liver cytosol stability of small molecules.

Over the last few decades, chemists have become skilled at designing compounds that avoid cytochrome P (CYP) 450 mediated metabolism. Typical screening assays are performed in liver microsomal fractions and it is possible to overlook the contribution of cytosolic enzymes until much later in the drug discovery process. Few data exist on cytosolic enzyme-mediated metabolism and no reliable tools are available to chemists to help design away from such liabilities. In this study, we screened 1450 compounds for liver cytosol-mediated metabolic stability and extracted transformation rules that might help medicinal chemists in optimizing compounds with these liabilities. In vitro half-life data were collected by performing in-house experiments in mouse (CD-1 male) and human (mixed gender) cytosol fractions. Matched molecular pairs analysis was performed in conjunction with qualitative-structure activity relationship modeling to identify chemical structure transformations affecting cytosolic stability. The transformation rules were prospectively validated on the test set. In addition, selected rules were validated on a diverse chemical library and the resulting pairs were experimentally tested to confirm whether the identified transformations could be generalized. The validation results, comprising nearly 250 library compounds and corresponding half-life data, are made publicly available. The datasets were also used to generate in silico classification models, based on different molecular descriptors and machine learning methods, to predict cytosol-mediated liabilities. To the best of our knowledge, this is the first systematic in silico effort to address cytosolic enzyme-mediated liabilities.

The use or generation of biomedical data and existing medicines to discover and establish new treatments for patients with rare diseases - recommendations of the IRDiRC Data Mining and Repurposing Task Force.

The number of available therapies for rare diseases remains low, as fewer than 6% of rare diseases have an approved treatment option. The International Rare Diseases Research Consortium (IRDiRC) set up the multi-stakeholder Data Mining and Repurposing (DMR) Task Force to examine the potential of applying biomedical data mining strategies to identify new opportunities to use existing pharmaceutical compounds in new ways and to accelerate the pace of drug development for rare disease patients. In reviewing past successes of data mining for drug repurposing, and planning for future biomedical research capacity, the DMR Task Force identified four strategic infrastructure investment areas to focus on in order to accelerate rare disease research productivity and drug development: (1) improving the capture and sharing of self-reported patient data, (2) better integration of existing research data, (3) increasing experimental testing capacity, and (4) sharing of rare disease research and development expertise. Additionally, the DMR Task Force also recommended a number of strategies to increase data mining and repurposing opportunities for rare diseases research as well as the development of individualized and precision medicine strategies.

Therapeutic effects of a small molecule agonist of the relaxin receptor ML290 in liver fibrosis.

Fibrosis is an underlying cause of cirrhosis and hepatic failure resulting in end stage liver disease with limited pharmacological options. The beneficial effects of relaxin peptide treatment were demonstrated in clinically relevant animal models of liver fibrosis. However, the use of relaxin is problematic because of a short half-life. The aim of this study was to test the therapeutic effects of recently identified small molecule agonists of the human relaxin receptor, relaxin family peptide receptor 1 (RXFP1). The lead compound of this series, ML290, was selected based on its effects on the expression of fibrosis-related genes in primary human stellate cells. RNA sequencing analysis of TGF-ß1-activated LX-2 cells showed that ML290 treatment primarily affected extracellular matrix remodeling and cytokine signaling, with expression profiles indicating an antifibrotic effect of ML290. ML290 treatment in human liver organoids with LPS-induced fibrotic phenotype resulted in a significant reduction of type I collagen. The pharmacokinetics of ML290 in mice demonstrated its high stability in vivo, as evidenced by the sustained concentrations of compound in the liver. In mice expressing human RXFP1 gene treated with carbon tetrachloride, ML290 significantly reduced collagen content, α-smooth muscle actin expression, and cell proliferation around portal ducts. In conclusion, ML290 demonstrated antifibrotic effects in liver fibrosis.-Kaftanovskaya, E. M., Ng, H. H., Soula, M., Rivas, B., Myhr, C., Ho, B. A., Cervantes, B. A., Shupe, T. D., Devarasetty, M., Hu, X., Xu, X., Patnaik, S., Wilson, K. J., Barnaeva, E., Ferrer, M., Southall, N. T., Marugan, J. J., Bishop, C. E., Agoulnik, I. U., Agoulnik, A. I. Therapeutic effects of a small molecule agonist of the relaxin receptor ML290 in liver fibrosis.

A randomized, proof-of-concept clinical trial on repurposing chlorcyclizine for the treatment of chronic hepatitis C.

BACKGROUND & AIMS: Chlorcyclizine HCl (CCZ) is a piperazine-class antihistamine with anti-hepatitis C virus (HCV) activity in vitro and in vivo. In a first-in-humans study for HCV, we evaluated the antiviral effects and safety of CCZ±ribavirin (RBV), characterized pharmacokinetic (PK) and viral kinetic (VK) patterns, and provide insights into CCZs mode of action against HCV. METHODS: Chronic HCV patients were randomized to CCZ (75 mg twice daily) or CCZ+weight-based RBV (1000/1200 mg daily) for 28 days. Therapy started with a loading dose of CCZ 150 mg ± RBV. Serial assessments of safety, liver tests, PK and VK markers were obtained. RESULTS: 24 HCV patients were treated; 54% male, median age 56 years, median HCV RNA 6.30 log IU/ml, without baseline differences between groups. At the end of therapy, subjects treated with CCZ monotherapy did not show any significant or sustained reduction in viremia (p = 0.69), whereas 7/12 (58%) subjects treated with CCZ+RBV had a >3-fold decline in HCV RNA. Subjects who responded demonstrated monophasic (n = 2), biphasic (n = 2) and triphasic (n = 3) VK responses. Contrary to historical RBV monotherapy response, CCZ+RBV demonstrated a continued viral decline suggesting a possible synergistic effect of CCZ+RBV. Mathematical modeling predicts a median effectiveness of CCZ+RBV in blocking viral production (ε) of 59% (Interquartile range, IQR: 50%) and blocking infection (η) of 78% (IQR: 23%). Adverse events (AEs) were mild-moderate without treatment discontinuations for AEs. CONCLUSIONS: In this human pilot study, CCZ demonstrated some anti-HCV effects, mostly in combination with RBV. More potent CCZ derivatives with optimal PK features may be more suitable for future therapeutic development. ClinicalTrials.gov number: NCT02118012.

Freedom of Information Act Access to an Investigational New Drug Application.

We report our experience working with the US Food and Drug Administration (FDA) to obtain access to an abandoned investigational new drug (IND) application and subsequent application documents submitted by Hoffman-La Roche, Inc. to the agency. Contrary to others' experience and in response to our specific request, FDA provided the IND application number and 464 pages of relevant material, including the initial pharmacology review by the agency and an annual report consisting of an investigational drug brochure, clinical study protocol and amendments and detailing clinical experience with drug treatment. It may be possible to bring application files of additional drugs previously submitted to the agency into the public record to help bolster repurposing efforts and realize our shared public interest in benefiting from previous human clinical studies.

Autocrine activation of JAK2 by IL-11 promotes platinum drug resistance.

Antineoplastic platinum agents are used in first-line treatment of ovarian cancer, but treatment failure frequently results from platinum drug resistance. Emerging observations suggest a role of reactive oxygen species (ROS) in the resistance of cancer drugs including platinum drugs. However, the molecular link between ROS and cellular survival pathway is poorly understood. Using quantitative high-throughput combinational screen (qHTCS) and genomic sequencing, we show that in platinum-resistant ovarian cancer elevated ROS levels sustain high level of IL-11 by stimulating FRA1-mediated IL-11 expression and increased IL-11 causes resistance to platinum drugs by constitutively activating JAK2-STAT5 via an autocrine mechanism. Inhibition of JAK2 by LY2784544 or IL-11 by anti-IL-11 antibody overcomes the platinum resistance in vitro or in vivo. Significantly, clinic studies also confirm the activated IL-11-JAK2 pathway in platinum-resistant ovarian cancer patients, which highly correlates with poor prognosis. These findings not only identify a novel ROS-IL-11-JAK2-mediated platinum resistance mechanism but also provide a new strategy for using LY2784544- or IL-11-mediated immunotherapy to treat platinum-resistant ovarian cancer.

Up-regulation of lysosomal TRPML1 channels is essential for lysosomal adaptation to nutrient starvation.

Upon nutrient starvation, autophagy digests unwanted cellular components to generate catabolites that are required for housekeeping biosynthesis processes. A complete execution of autophagy demands an enhancement in lysosome function and biogenesis to match the increase in autophagosome formation. Here, we report that mucolipin-1 (also known as TRPML1 or ML1), a Ca(2+) channel in the lysosome that regulates many aspects of lysosomal trafficking, plays a central role in this quality-control process. By using Ca(2+) imaging and whole-lysosome patch clamping, lysosomal Ca(2+) release and ML1 currents were detected within hours of nutrient starvation and were potently up-regulated. In contrast, lysosomal Na(+)-selective currents were not up-regulated. Inhibition of mammalian target of rapamycin (mTOR) or activation of transcription factor EB (TFEB) mimicked a starvation effect in fed cells. The starvation effect also included an increase in lysosomal proteostasis and enhanced clearance of lysosomal storage, including cholesterol accumulation in Niemann-Pick disease type C (NPC) cells. However, this effect was not observed when ML1 was pharmacologically inhibited or genetically deleted. Furthermore, overexpression of ML1 mimicked the starvation effect. Hence, lysosomal adaptation to environmental cues such as nutrient levels requires mTOR/TFEB-dependent, lysosome-to-nucleus regulation of lysosomal ML1 channels and Ca(2+) signaling.

Discovery and characterization of a G protein-biased agonist that inhibits ß-arrestin recruitment to the D2 dopamine receptor.

A high-throughput screening campaign was conducted to interrogate a 380,000+ small-molecule library for novel D2 dopamine receptor modulators using a calcium mobilization assay. Active agonist compounds from the primary screen were examined for orthogonal D2 dopamine receptor signaling activities including cAMP modulation and ß-arrestin recruitment. Although the majority of the subsequently confirmed hits activated all signaling pathways tested, several compounds showed a diminished ability to stimulate ß-arrestin recruitment. One such compound (MLS1547; 5-chloro-7-[(4-pyridin-2-ylpiperazin-1-yl)methyl]quinolin-8-ol) is a highly efficacious agonist at D2 receptor-mediated G protein-linked signaling, but does not recruit ß-arrestin as demonstrated using two different assays. This compound does, however, antagonize dopamine-stimulated ß-arrestin recruitment to the D2 receptor. In an effort to investigate the chemical scaffold of MLS1547 further, we characterized a set of 24 analogs of MLS1547 with respect to their ability to inhibit cAMP accumulation or stimulate ß-arrestin recruitment. A number of the analogs were similar to MLS1547 in that they displayed agonist activity for inhibiting cAMP accumulation, but did not stimulate ß-arrestin recruitment (i.e., they were highly biased). In contrast, other analogs displayed various degrees of G protein signaling bias. These results provided the basis to use pharmacophore modeling and molecular docking analyses to build a preliminary structure-activity relationship of the functionally selective properties of this series of compounds. In summary, we have identified and characterized a novel G protein-biased agonist of the D2 dopamine receptor and identified structural features that may contribute to its biased signaling properties.

Small-molecule agonists for the thyrotropin receptor stimulate thyroid function in human thyrocytes and mice.

Seven-transmembrane-spanning receptors (7TMRs) are prominent drug targets. However, small-molecule ligands for 7-transmembrane-spanning receptors for which the natural ligands are large, heterodimeric glycoprotein hormones, like thyroid-stimulating hormone (TSH; thyrotropin), have only recently been reported, and none are approved for human use. We have used quantitative high-throughput screening to identify a small-molecule TSH receptor (TSHR) agonist that was modified to produce a second agonist with increased potency. We show that these agonists are highly selective for human TSHR versus other glycoprotein hormone receptors and interact with the receptor's serpentine domain. A binding pocket within the transmembrane domain was defined by docking into a TSHR homology model and was supported by site-directed mutagenesis. In primary cultures of human thyrocytes, both TSH and the agonists increase mRNA levels for thyroglobulin, thyroperoxidase, sodium iodide symporter, and deiodinase type 2, and deiodinase type 2 enzyme activity. Moreover, oral administration of the agonist stimulated thyroid function in mice, resulting in increased serum thyroxine and thyroidal radioiodide uptake. Thus, we discovered a small molecule that activates human TSHR in vitro, is orally active in mice, and could be a lead for development of drugs to use in place of recombinant human TSH in patients with thyroid cancer.

A basis for reduced chemical library inhibition of firefly luciferase obtained from directed evolution.

We measured the "druggability" of the ATP-dependent luciferase derived from the firefly Photuris pennsylvanica that was optimized using directed evolution (Ultra-Glo, Promega). Quantitative high-throughput screening (qHTS) was used to determine IC(50)s of 198899 samples against a formulation of Ultra-Glo luciferase (Kinase-Glo). We found that only 0.1% of the Kinase-Glo inhibitors showed an IC(50) < 10 microM compared to 0.9% found from a previous qHTS against the firefly luciferase from Photinus pyralis (lucPpy). Further, the maximum affinity identified in the lucPpy qHTS was 50 nM, while for Kinase-Glo this value increased to 600 nM. Compounds with interactions stretching outside the luciferin binding pocket were largely lost with Ultra-Glo luciferase. Therefore, Ultra-Glo luciferase will show less compound interference when used as an ATP sensor compared to lucPpy. This study demonstrates the power of large-scale quantitative analysis of structure-activity relationships (>100K compounds) in addressing important questions such as a target's druggability.

Fluorescence spectroscopic profiling of compound libraries.

Chromo/fluorophoric properties often accompany the heterocyclic scaffolds and impurities that comprise libraries used for high-throughput screening (HTS). These properties affect assay outputs obtained with optical detection, thus complicating analysis and leading to false positives and negatives. Here, we report the fluorescence profile of more than 70,000 samples across spectral regions commonly utilized in HTS. The quantitative HTS paradigm was utilized to test each sample at seven or more concentrations over a 4-log range in 1,536-well format. Raw fluorescence was compared with fluorophore standards to compute a normalized response as a function of concentration and spectral region. More than 5% of library members were brighter than the equivalent of 10 nM 4-methyl umbelliferone, a common UV-active probe. Red-shifting the spectral window by as little as 100 nm was accompanied by a dramatic decrease in autofluorescence. Native compound fluorescence, fluorescent impurities, novel fluorescent compounds, and the utilization of fluorescence profiling data are discussed.

Characterization of chemical libraries for luciferase inhibitory activity.

To aid in the interpretation of high-throughput screening (HTS) results derived from luciferase-based assays, we used quantitative HTS, an approach that defines the concentration-response behavior of each library sample, to profile the ATP-dependent luciferase from Photinus pyralis against more than 70,000 samples. We found that approximately 3% of the library was active, containing only compounds with inhibitory concentration-responses, of which 681 (0.9%) exhibited IC 50 < 10 microM. Representative compounds were shown to inhibit purified P. pyralis as well as several commercial luciferase-based detection reagents but were found to be largely inactive against Renilla reniformis luciferase. Light attenuation by the samples was also examined and found to be more prominent in the blue-shifted bioluminescence produced by R. reniformis luciferase than in the bioluminescence produced by P. pyralis luciferase. We describe the structure-activity relationship of the luciferase inhibitors and discuss the use of this data in the interpretation of HTS results and configuration of luciferase-based assays.

Kinase patent space visualization using chemical replacements.

Here we present a methodology for characterizing the structure of patented chemical space. This approach identifies those chemical replacements that can connect sets of exemplified compounds in individual patents. Chemists can then search these replacements to help them discover the architecture within their patent space of interest. To demonstrate the utility of such an approach, we characterize a set of kinase inhibitors from patents and literature and find that many companies' patents can be understood to be straightforward modifications of competitors' patents. By reapplying these same chemical themes to other related compound series, novel, biologically active compounds can be discovered.

Potential of mean force between two hydrophobic solutes in water.

We study the potential of mean force between two nonpolar solutes in the Mercedes Benz model of water. Using NPT Monte Carlo simulations, we find that the solute size determines the relative preference of two solute molecules to come into contact ('contact minimum') or to be separated by a single layer of water ('solvent-separated minimum'). Larger solutes more strongly prefer the contacting state, while smaller solutes have more tendency to become solvent-separated, particularly in cold water. The thermal driving forces oscillate with solute separation. Contacts are stabilized by entropy, whereas solvent-separated solute pairing is stabilized by enthalpy. The free energy of interaction for small solutes is well-approximated by scaled-particle theory.